募集情報Job Information
Forward-Deployed Data Scientist（顧客対応型データサイエンティスト）
Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:
・Design RL use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
・Build and own the full ML pipeline — taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
・Drive customer success by being providing ongoing technical guidance that ensures data science performance, successful adoption and measurable outcomes
・Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
・Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
・Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table
- WHAT YOU HAVE
– Education:
Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred– Experience:
3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred– Strong technical expertise:
Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment– Engineering best practices:
You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions– Nice-to-have skills:
Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms– Customer collaborator:
Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value– Entrepreneurial problem-solver:
You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions– Continuous learner:
You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow– Clear communicator:
Able to explain complex technical ideas persuasively to both technical and non-technical audiences
募集要項
- WHAT YOU'LL DO
- Our Data Scientist, AI Deployment team is a group of creative technical experts who design and build end-to-end machine learning solutions that power 1-to-1 personalization for some of the world's leading brands. In this role, you will:
・Design RL use cases from the ground up — scoping solutions that optimize for real business value, accounting for the complexity of modern marketing journeys, and proactively identifying risks to set each engagement up for success
・Build and own the full ML pipeline — taking customers' raw data through transformation, model training, and activation, so that model decisions are delivered to personalize experiences for millions of end users
・Drive customer success by being providing ongoing technical guidance that ensures data science performance, successful adoption and measurable outcomes
・Extend product capabilities by developing features and tools that support the broader AI deployment team and scale what's possible across engagements
・Partner with the Braze Product team to refine and advance Braze's reinforcement learning algorithms, pushing the self-learning capabilities of the platform forward
・Shape BrazeAI product strategy and roadmap by bringing customer-facing insights and deep technical expertise to the table - WHAT WE OFFER
- 様々なライフステージをサポートする包括的な福利厚生からハイブリットワークまで、仕事と私生活のバランスをとるために必要なものを提供しています。
■長期的な資産形成
・競争力のある報酬
・401K / 企業型確定拠出年金
・従業員株式購入制度 (ESPP)
・Financial Coaching を受ける機会
■キャリア構築 / 育成サポート
・学習費用補助制度
・Development / Coaching / カウンセリングなどを受ける機会
・個人、チーム、ビジネスの成長とともに創出されるキャリアパス
・その他社内の学習プラットフォームや、LinkedIn Learning などのアクセス
■健康 / 家族サポート
・医療費用補助
・休暇制度
・Fertility & Family Forming Support
■チームビルディングの機会
・Volunteer Activity
・Braze 内で支援コミュニティを構築する従業員リソースグループ
・毎週水曜日の Office Lunch Offering
・他部署とのランチ会
・Referral Program
・その他 Global とのチームビルディングや様々な機会を通して、チーム間の価値観の理解や繋がり構築に取り組めるようにしています。
■その他
・WorkStyling 全拠点アクセス
・オフィスの Drinks & Snacks - ABOUT BRAZE
- Braze (Nasdaq) は、顧客とブランドの良質な関係構築を支援するカスタマーエンゲージメントプラットフォームを提供しています。海外ではBurger King、KFC、McDonarld、Mercari、PizzaHut、SEPHORA、日本ではメルカリ、タイミー、コスモ石油、マネーフォワード、freee、サンリオ、ミスミ等で活用されています。
データ発生から1.1秒でマーケティング施策に活用でき、生成AIを活用したパーソナライズコミュニケーションを支援し、店舗・ウェブ・アプリとマルチに広がるチャネルに対応した一貫した人間らしいデジタル体験を提供し、ブランドと消費者の結びつきを強くし、収益とブランド価値強化の双方を実現します。テクノロジーとクリエイティビィティーが融合させるマーケティング5.0の実現インフラといっても過言ではありません。
Braze は米国と英国でGreat Place to Work®として認定されており、2022 年、Braze はニューヨークのFortune's Best Small and Medium Workplaces で1 位、アメリカのFortune's Best Workplaces for Millennials で5 位、イギリスのFortune's Best Medium Sized Workplaces for Women で11 位を獲得しました。
ニューヨークの本社をはじめ、東京以外にもオースティン、ベルリン、シカゴ、ロンドン、パリ、サンフランシスコ、シンガポール、トロントなど、世界各地で多くの社員が働いています。
Braze株式会社
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